Previously, a Gaussian assumption has been applied to an interference signal in order to operate a system, such as Adaptive Modulation and Coding (AMC), the generation of a soft decision decoding metric, or the like, with a low level of complexity. Accordingly, a Quadrature Amplitude Modulation (QAM)-based modulation scheme has been mainly used to cause a characteristic of an interference signal to be as close as possible to a Gaussian characteristic.
However, a non-Gaussian channel has a channel capacity larger than that of a Gaussian channel. Accordingly, when a statistical characteristic of an interference signal is appropriately reflected during the operation of a system, network throughput can be obtained which is higher over a non-Gaussian channel than over a Gaussian channel. In this regard, it has been required to develop a modulation scheme which allows an interference signal to have a non-Gaussian characteristic, and thus a modulation scheme proposed according the requirement is a Frequency and Quadrature Amplitude Modulation (FQAM) scheme.
FIG. 1 is a view for explaining the concept of FQAM. Referring to FIG. 1, FQAM is a modulation scheme obtained by combining QAM with Frequency-Shift Keying (FSK), and has a characteristic which causes a characteristic of Inter-Cell Interference (ICI) signal to be non-Gaussian, similarly to a case of FSK. Also, FQAM simultaneously uses the QAM scheme, and thus can greatly improve spectral efficiency, as compared with the FSK scheme.
When a statistical characteristic of an interference signal is non-Gaussianized due to the application of a modulation scheme such as FQAM, it is difficult to apply an operation scheme of AMC technology, which is designed based on a Gaussian channel of the related art, and a method for generating a soft decision decoding metric.
The AMC technology is a scheme in which a channel state of itself is observed, a channel capacity is predicted based on the observed channel state, and an optimal modulation order and an optimal coding rate are applied. The AMC scheme designed based on a Gaussian channel determines an optimal modulation order and an optimal coding rate mainly by using a Signal-to-Noise Ratio (SNR). This is because, in the case of a Gaussian channel, a channel capacity can be predicted depending on an SNR. In contrast, in the case of a non-Gaussian channel, a channel capacity greatly changes depending on not only an SNR but also the degree of non-Gaussianization of a channel, and thus it is necessary to estimate the degree of non-Gaussianization of a channel.
Also, it is well-known that the decoding performance of a system is significantly degraded when a Gaussian soft decision metric is applied to a situation in which a statistical characteristic of an interference signal has a non-Gaussian characteristic. Accordingly, when a statistical characteristic of an interference signal is non-Gaussianized due to the application of a modulation scheme such as FQAM, it is necessary to reflect the degree of non-Gaussianization of a channel during the generation of a soft decision decoding metric. As a result, even when the soft decision decoding metric is generated, a process for estimating the non-Gaussianization of a channel is required.